Eavesdrop the Composition Proportion of Training Labels in Federated
Learning

Eavesdrop the Composition Proportion of Training Labels in Federated Learning

14 October 2019

Papers citing "Eavesdrop the Composition Proportion of Training Labels in Federated Learning"

15 / 15 papers shown

Title
FRIDA: Free-Rider Detection using Privacy Attacks Pol G. Recasens Ádám Horváth Alberto Gutierrez-Torre Jordi Torres Josep Ll. Berral Balázs Pejó FedML 24 0 0 07 Oct 2024
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 30 23 0 20 Jul 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 16 4 0 06 Jun 2023
A Survey on Class Imbalance in Federated Learning Jing Zhang Chuanwen Li Jianzgong Qi Jiayuan He FedML 39 13 0 21 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 76 47 0 21 Feb 2023
How to Combine Membership-Inference Attacks on Multiple Updated Models Matthew Jagielski Stanley Wu Alina Oprea Jonathan R. Ullman Roxana Geambasu 21 10 0 12 May 2022
Federated Class-Incremental Learning Jiahua Dong Lixu Wang Zhen Fang Gan Sun Shichao Xu Xiao Wang Qi Zhu CLL FedML 22 168 0 22 Mar 2022
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection Phillip Rieger T. D. Nguyen Markus Miettinen A. Sadeghi FedML AAML 17 150 0 03 Jan 2022
A Field Guide to Federated Optimization Jianyu Wang Zachary B. Charles Zheng Xu Gauri Joshi H. B. McMahan ... Mi Zhang Tong Zhang Chunxiang Zheng Chen Zhu Wennan Zhu FedML 173 411 0 14 Jul 2021
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization Lixu Wang Shichao Xu Ruiqi Xu Xiao Wang Qi Zhu AAML 11 45 0 13 Jun 2021
Property Inference Attacks on Convolutional Neural Networks: Influence and Implications of Target Model's Complexity Mathias Parisot Balázs Pejó Dayana Spagnuelo MIACV 19 33 0 27 Apr 2021
FLAME: Taming Backdoors in Federated Learning (Extended Version 1) T. D. Nguyen Phillip Rieger Huili Chen Hossein Yalame Helen Mollering ... Azalia Mirhoseini S. Zeitouni F. Koushanfar A. Sadeghi T. Schneider AAML 19 26 0 06 Jan 2021
An Exploratory Analysis on Users' Contributions in Federated Learning Jiyue Huang Rania Talbi Zilong Zhao S. Bouchenak L. Chen Stefanie Roos FedML 18 30 0 13 Nov 2020
Quality Inference in Federated Learning with Secure Aggregation Balázs Pejó G. Biczók FedML 19 22 0 13 Jul 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,032 0 29 Nov 2018